[PDF][PDF] The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review
People in the modern era spend most of their lives in virtual environments that offer a range
of public and private services and social platforms. Therefore, these environments need to …
of public and private services and social platforms. Therefore, these environments need to …
The ethical implications of artificial intelligence (AI) for meaningful work
The increasing workplace use of artificially intelligent (AI) technologies has implications for
the experience of meaningful human work. Meaningful work refers to the perception that …
the experience of meaningful human work. Meaningful work refers to the perception that …
Ethical dilemmas and privacy issues in emerging technologies: A review
Industry 5.0 is projected to be an exemplary improvement in digital transformation allowing
for mass customization and production efficiencies using emerging technologies such as …
for mass customization and production efficiencies using emerging technologies such as …
[HTML][HTML] Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing
Network traffic analysis is an important cybersecurity task, which helps to classify
anomalous, potentially dangerous connections. In many cases, it is critical not only to detect …
anomalous, potentially dangerous connections. In many cases, it is critical not only to detect …
A Digital Competence Framework for Learners (DCFL): A Conceptual Framework for Digital Literacy.
Digital technologies are the main driver of the future economy, with technology jobs and
those requiring digital skills on the rise. In educational settings, there is an accelerated …
those requiring digital skills on the rise. In educational settings, there is an accelerated …
Responsible natural language processing: A principlist framework for social benefits
Businesses harness the power of natural language processing (NLP) to automate processes
and make data-driven decisions. However, NLP raises concerns on a number of fronts due …
and make data-driven decisions. However, NLP raises concerns on a number of fronts due …
Artificial intelligence for cyber security: Current trends and future challenges
Artificial intelligence (AI) has helped industries and society today to become modern and
more productive. Using the Internet of Things (IoT), we can sense and transfer data through …
more productive. Using the Internet of Things (IoT), we can sense and transfer data through …
Review of AI and machine learning applications to predict and Thwart cyber-attacks in real-time
The contemporary cybersecurity landscape demands innovative solutions to combat the
relentless evolution of cyber threats. Traditional approaches are facing unprecedented …
relentless evolution of cyber threats. Traditional approaches are facing unprecedented …
[HTML][HTML] Ethical principles sha** values-based cybersecurity decision-making
J Fenech, D Richards, P Formosa - Computers & Security, 2024 - Elsevier
The human factor in information systems is a large vulnerability when implementing
cybersecurity, and many approaches, including technical and policy driven solutions, seek …
cybersecurity, and many approaches, including technical and policy driven solutions, seek …
[HTML][HTML] Coordinated vulnerability disclosure programme effectiveness: Issues and recommendations
T Walshe, AC Simpson - Computers & Security, 2022 - Elsevier
Abstract Coordinated Vulnerability Disclosure (CVD) programmes leverage a global network
of independent security researchers (hackers) to support pre-and post-deployment security …
of independent security researchers (hackers) to support pre-and post-deployment security …